1. Technical Field
The present invention relates generally to computer network security and, more specifically, to a system and method for user friendly detection of spammers.
2. Description of the Related Art
During the last decade, many different approaches for sharing photographic, audio, and video content over a network have been developed. Content sharing portals implementing these approaches are convenient because the portals allow users to easily share data with others. However, content sharing portals are also used by automated spammers to send junk messages to many different email addresses. The spammers harm the brand of the service provider and are costly, in terms of time and resources, to the end-users and service providers of email addresses.
To prevent spammers from accessing content sharing services, many content sharing portals require users to solve a CAPTCHA (“Completely Automated Public Turing test to tell Computers and Humans Apart”) or reverse-Turing problem, a problem that is solvable by a human but not by a machine, as part of the registration process. An exemplary CAPTCHA problem asks a user to decipher a word written in warped text having a distorted background. Theoretically, any adult human computer user can solve a CAPTCHA problem, but a machine cannot do so in a reasonable amount of time.
The CAPTCHA/reverse-Turing approach has been effective in preventing many spammers from accessing content sharing portals. However, this approach suffers from several drawbacks. First, CAPTCHA problems are not user-friendly to the degree that CAPTCHA problems add an extra step to the registration process and require mental effort. Second, due to improvements in processing speed and artificial intelligence technologies, machines are now able to solve many traditionally-reverse-Turing problems, thereby rendering these reverse-Turing tests obsolete and allowing spammers to register with content sharing portals implementing these tests.
As the foregoing illustrates, what is needed in the art is a more user-friendly and more effective technique for identifying spammers.